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Performance of RM3 Weather Forecasts over West Africa during June - September 2011 David Liebers, Kush Dave, Dr. Gerald K.F. Rabl, Dr. Leonard M. Druyan,

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Presentation on theme: "Performance of RM3 Weather Forecasts over West Africa during June - September 2011 David Liebers, Kush Dave, Dr. Gerald K.F. Rabl, Dr. Leonard M. Druyan,"— Presentation transcript:

1 Performance of RM3 Weather Forecasts over West Africa during June - September 2011 David Liebers, Kush Dave, Dr. Gerald K.F. Rabl, Dr. Leonard M. Druyan, Dr. Matthew B. Fulakeza, Ruben Worrell Abstract. The West African Monsoon is a climatological moisture system in the Sahel region of Western Africa. The rainfall follows a cyclic pattern of moisture that shifts north and south seasonally, which supplies the annual source of precipitation to this area during the summer months of June through September. The Regional Model (RM3) at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (GISS) is producing weather forecasts for West Africa. RM3 daily forecast simulations for rainfall, minimum and maximum surface air temperature extracted at specific locations corresponding to 36 weather stations in the West African region are validated against the stations’ measurements. Furthermore, daily mean precipitation and surface air temperature forecasts by the RM3 are validated against TRMM (Tropical Rainfall Measuring Mission) and NCEP (National Centers for Environmental Prediction) Reanalysis 2 over the season June through September 2011. The validation also considers the time correlation between model and observed parameters throughout the whole season. We found areas with good prediction of seasonal trends and relatively high correlation in the daily prediction as well as areas where the RM3 simulation outcome is relatively poor. Table 1: Summary of the 36 West African stations used in this study, listed by decreasing geographical latitude. References Druyan, L.M., and M. Fulakeza, 2012: Regional climate model applications for West Africa and the Tropical Eastern Atlantic. In Climate Models. L.M. Druyan, Ed. InTech, pp. 43-58. Druyan, L.M., M. Fulakeza, and P. Lonergan, 2010: Regional model nesting within GFS daily forecasts over West Africa Open. Atmos. Sci. J., 4, 1-11. Jenkins G.M., and D.G. Watts, Spectral Analysis and its Applications, Holden Day, San Francisco, 1968. Analysis. This study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies. The performance of the RM3 for forecast and climate simulations over the entire West African region has been evaluated and validated by a variety of papers (e.g., Druyan and Fulakeza, 2012). The major goal of this investigation is to analyze the performance of the RM3 daily weather forecast model at specific locations corresponding to a selection of weather stations distributed over West Africa. Thus, we compare and contrast the RM3 simulated outcome with station measurements of rainfall, minimum and maximum surface temperature, respectively, during the monsoon season from June through September (JJAS) 2011. We also compare the modeled RM3 forecast data and stations measurements with TRMM (rainfall) and NCEP Reanalysis 2 (minimum and maximum temperature) data. The analysis involves comparison of regional RM3 forecasts averaged over the entire season, and statistically tests the quality of the forecast simulations by using monthly averages as well as cross correlation analysis based on the given daily time series (Fig.1). Analysis Approach. Visual examination of the time series as shown in Fig. 1 provided a first overall picture of the quality of the RM3 simulations. Then, monthly rainfall JJAS average histograms for each individual station were analyzed in order to find regions or areas with common patterns or differences in the RM3 simulations as well as in the observed rainfall data (Fig.2). Following this procedure, we identified five regions, where the RM3 and stations averages either demonstrated a similar JJAS trend or discrepancy. The outcome yielded 5 regions as shown in Fig.3. Sponsors: The authors wish to thank NASA New York City Research Initiative (NYCRI) NASA Goddard Institute for Space Studies (GISS) NASA Goddard Space Flight Center (GSFC) National Science Foundation (NSF) Contributors: (2012) David L iebers [Undergraduate Student] Kush Dave [HS Student] Dr. Gerald K.F. Rabl [HS and College Teacher] Dr. Leonard M. Druyan [Team P.I.] Dr. Matthew B. Fulakeza [Team P.I.] Ruben Worrell [Education Specialist] Figure 3: Overview of regional distribution of stations for which daily rainfall, maximum and minimum daily temperature were available with at least 20 measurements per month. Also shown are regions 1-5. Figure 1: Time series of three selected stations comparing station measurements (blue) with RM3 data (red) for rainfall (top panel), minimum temperature (middle panel), and maximum temperature (bottom panel). The time span covers the four month season from June 1 - September 30, 2011. Figure 4: Errors in RM3 vs. station-based measurements of average precipitation (mm/day) at selected stations superimposed on corresponding TRMM measurements during JJAS 2011. Note that RM3 errors are given in mm/day, while TRMM measurements display the JJAS (mm) seasonal accumulation. Results. The mean minimum and mean maximum error plots in the north and south central regions of West Africa reveal that the model predicts colder temperatures throughout the course of the monsoon season. Conversely, the temperatures along the western coast of the Sahel demonstrate a closer correlation to RM3. The mean precipitation also reveals a flaw in the north and south central regions of the Sahel zone as well as the western coast. Additionally, the RM3 model predicted a much rainier monsoon season for the southern west coast (Figs. 5-6). Figure 5: Errors in RM3 vs. station-based measurements of average minimum surface air temperature (  C) at selected stations superimposed on corresponding NCEP Reanalysis 2 horizontal distribution mean minimum surface air temperature (Kelvin) during JJAS 2011. Figure 6: Errors in RM3 vs. station-based measurements of average maximum surface air temperature (  C) at selected stations superimposed on corresponding NCEP Reanalysis 2 horizontal distribution mean maximum surface air temperature (Kelvin) during JJAS 2011. Data Selection. Rainfall, minimum and maximum temperature measurements were available from 56 stations located in the West African region during the time interval June 1 - September 30, 2011. However, many of these 56 original stations were missing data on many days throughout the interval of investigation. In order to obtain viable data sets for a forecast analysis and reliable statistical study, we only used stations that contained at least 20 measurements per month, recorded for both RM3 and ACMAD. Table 1 lists the remaining 36 stations used in this study, while Fig.3 displays the geographical distribution of the stations in the West African region. For each region shown in Fig.3, monthly averages were calculated for rainfall, min. and max. temperature for stations, RM3, TRMM, and NCEP Reanalysis 2 data. Although there are some differences and discrepancies between averages computed from RM3 simulations and actual measurements, the overall simulated RM3 trend is in good accordance with observed averages throughout the entire JJAS season (Fig.7). Figure 7: The histograms compare the monthly average rainfall (mm/day) throughout the JJAS months as measured at stations (blue), observed by TRMM (red) and predicted by RM3 (green) for each of the regions 1-4 as displayed in Fig.3. Figure 8: The top panel displays the maximum surface air temperature time series as observed (blue) and RM3-predicted (red) at Berberati. The bottom panels show the linear cross correlation result between observed and predicted temperature (left), and the correlation result (in terms of standard deviation  ) for the detrended (prewhitened) time series (right). The forecast simulation is related to the observed maximum surface air temperature at a 3  level. Linear cross correlations were computed between observed and RM3 predicted time series to analyze the day-by-day performance of RM3 (Fig.8). In order to make an unbiased estimate of the statistical significance of the correlations, the time series were prewhitened to remove the tendency in all of the data sets for adjacent points in the same data set to be highly correlated (Jenkins and Watts, 1968). This procedure eliminates artificially large correlations that can arise between two non-prewhitened time series. Conclusion/Future Research. Generally RM3 seems to correlate closely with the seasonal rainfall trends, although there are daily discrepancies between observed and modeled rainfall scenarios. The RM3 seems to overestimate monthly rainfall mostly at lower northern geographical latitudes (near the equator) and underestimate monthly rainfall in the central and northern regions of western Africa. The model also seems to correctly predict seasonal trends in temperature, especially along the west coast where sea surface temperatures rarely fluctuate. Still, discrepancies do exist between observed and modeled rainfall. RM3 seems underestimate mean minimum surface air temperature for most of the regions, more so in the northwestern and southwestern area. Future research and investigation should include better station coverage and a better station distribution in the West African region. Figure 2: Representative example of monthly JJAS rainfall averages for four stations. All four stations exhibit a similar seasonal pattern, which was used to define region 4. Thus, all stations in region 4 show similar seasonal structure as the examples shown above.


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